Search engines are used in computing applications to find files, documents or internet web pages by using text search terms. A search term may be a single word or term or a phrase or other plurality of words, and search engines use a variety of methodology to find results relevant to the term, including searching file and web page names, text content and other associated text information such as embedded tags. A vast amount of data is generally available for search and retrieval by a search engine, including files and text data residing upon local computers or devices, local area networks (LAN), wide area network (WAN), and internet and intranet networked computer resources and their associated storage devices. Thus, finding data relevant to a search term is generally not a challenge. Problems arise instead in identifying and presenting the most relevant data to a search engine user in an efficient manner.
Although preferred search results for a given search may be defined by a number of limiting parameters, in order to ensure finding preferred results a successful search usually starts with a broad search term. Broad search terms generally return a vast plurality of results of divergent types, quality and relevance to the search target, particularly when the internet is included within the search domain. Thus, initial search engine results must often be refined by revising search terms to include or exclude one or more search words or parameters, with refined search results generated through initiating additional narrowing searches, often through multiple search term entry and search initiation iterations.
Each new search iteration generally requires a user to navigate a device display screen cursor to a search engine dialog box with a mouse or other pointer device, type in new search terms through keystroke methods, and then initiate the new search by some other keyboard or pointer device input, which often requires still further navigation of the screen cursor to another search-initiation icon located at another area of the screen. Such keyboarding and cursor guiding activities may be especially cumbersome, time-consuming and annoying to users, and in particular to users with low keyboarding skills or disabilities that may interfere with or encumber keyboarding tasks.
Some prior art search engines attempt to improve the search experience by improving subsequent searching efficiencies and keyboarding tasks by analyzing search terms and/or search results and providing hyperlinked lists of suggested substitute search terms words, or links to other specialized internet search engines, that appear most relevant through said analysis. Such suggested search modifications or link referrals are intended to enable a user to avoid retyping new search terms, and instead initiate a subsequent search by simply clicking on one of the proffered links. However, the ability to accurately predict a user's preferred search results and thereby generate relevant suggested links or substitute search terms from a simple broad term is limited, particularly in the case of very broad search terms, and often suggested terms and links are unsatisfactorily off-target. And commercial search engines generally bias links and suggested search term toward paid advertisers or other entities that pay the search engine provider for inclusion, at the exclusions of other and perhaps better non-commercial or non-client links and web providers. Thus, it is common for none of the suggested new search terms or proffered web page links provided by the prior art to appear relevant to the user's search objective, who must instead again keyboard in a new search term and start searching again.
Unsatisfactory and cumbersome search engine use experiences may drive a user to try another search engine provider, resulting in a loss of web-based advertising revenue to an abandoned search engine provider.